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Category:
Language:
English
Total Size:
7.3 GB
Info Hash:
9FFA9F66F6666692D9F6ACEBF61B486AD7359B2F
Added By:
Added:
Oct. 25, 2023, 11:32 p.m.
Stats:
|
(Last updated: May 18, 2025, 3:41 p.m.)
| File | Size |
|---|---|
| 2. Windows-Focused Environment Setup 2018.mp4 | 180.7 MB |
| READ_ME.txt | 404 bytes |
| 1. Welcome.mp4 | 35.7 MB |
| 1. Welcome.srt | 5.7 KB |
| 2. Overview and Outline.mp4 | 79.7 MB |
| 2. Overview and Outline.srt | 17.7 KB |
| 3. Where to get the Code.mp4 | 30.2 MB |
| 3. Where to get the Code.srt | 7.6 KB |
| 1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 | 60.5 MB |
| 1. Intro to Google Colab, how to use a GPU or TPU for free.srt | 14.3 KB |
| 2. Uploading your own data to Google Colab.mp4 | 90.5 MB |
| 2. Uploading your own data to Google Colab.srt | 14.5 KB |
| 3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 | 44.4 MB |
| 3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.srt | 12.1 KB |
| 1. What is Machine Learning.mp4 | 70.6 MB |
| 1. What is Machine Learning.srt | 18.4 KB |
| 2. Regression Basics.mp4 | 73.0 MB |
| 2. Regression Basics.srt | 20.1 KB |
| 3. Regression Code Preparation.mp4 | 45.5 MB |
| 3. Regression Code Preparation.srt | 16.4 KB |
| 4. Regression Notebook.mp4 | 71.9 MB |
| 4. Regression Notebook.srt | 17.5 KB |
| 5. Moore's Law.mp4 | 30.6 MB |
| 5. Moore's Law.srt | 9.1 KB |
| 6. Moore's Law Notebook.mp4 | 78.9 MB |
| 6. Moore's Law Notebook.srt | 15.8 KB |
| 7. Linear Classification Basics.mp4 | 67.2 MB |
| 7. Linear Classification Basics.srt | 19.8 KB |
| 8. Classification Code Preparation.mp4 | 26.5 MB |
| 8. Classification Code Preparation.srt | 9.4 KB |
| 9. Classification Notebook.mp4 | 78.3 MB |
| 9. Classification Notebook.srt | 14.6 KB |
| 10. Saving and Loading a Model.mp4 | 28.8 MB |
| 10. Saving and Loading a Model.srt | 6.6 KB |
| 11. A Short Neuroscience Primer.mp4 | 44.7 MB |
| 11. A Short Neuroscience Primer.srt | 12.3 KB |
| 12. How does a model learn.mp4 | 50.1 MB |
| 12. How does a model learn.srt | 13.8 KB |
| 13. Model With Logits.mp4 | 27.3 MB |
| 13. Model With Logits.srt | 5.3 KB |
| 14. Train Sets vs. Validation Sets vs. Test Sets.mp4 | 52.1 MB |
| 14. Train Sets vs. Validation Sets vs. Test Sets.srt | 14.3 KB |
| 1. Artificial Neural Networks Section Introduction.mp4 | 33.5 MB |
| 1. Artificial Neural Networks Section Introduction.srt | 7.9 KB |
| 2. Forward Propagation.mp4 | 47.1 MB |
| 2. Forward Propagation.srt | 12.2 KB |
| 3. The Geometrical Picture.mp4 | 56.4 MB |
| 3. The Geometrical Picture.srt | 11.5 KB |
| 4. Activation Functions.mp4 | 89.2 MB |
| 4. Activation Functions.srt | 22.6 KB |
| 5. Multiclass Classification.mp4 | 48.7 MB |
| 5. Multiclass Classification.srt | 12.2 KB |
| 6. How to Represent Images.mp4 | 75.4 MB |
| 6. How to Represent Images.srt | 15.3 KB |
| 7. Code Preparation (ANN).mp4 | 67.5 MB |
| 7. Code Preparation (ANN).srt | 19.9 KB |
| 8. ANN for Image Classification.mp4 | 106.3 MB |
| 8. ANN for Image Classification.srt | 22.6 KB |
| 9. ANN for Regression.mp4 | 80.2 MB |
| 9. ANN for Regression.srt | 13.0 KB |
| 1. What is Convolution (part 1).mp4 | 79.7 MB |
| 1. What is Convolution (part 1).srt | 20.1 KB |
| 2. What is Convolution (part 2).mp4 | 24.5 MB |
| 2. What is Convolution (part 2).srt | 7.2 KB |
| 3. What is Convolution (part 3).mp4 | 28.7 MB |
| 3. What is Convolution (part 3).srt | 8.0 KB |
| 4. Convolution on Color Images.mp4 | 76.4 MB |
| 4. Convolution on Color Images.srt | 20.8 KB |
| 5. CNN Architecture.mp4 | 89.5 MB |
| 5. CNN Architecture.srt | 27.8 KB |
| 6. CNN Code Preparation (part 1).mp4 | 76.7 MB |
| 6. CNN Code Preparation (part 1).srt | 22.8 KB |
| 7. CNN Code Preparation (part 2).mp4 | 36.7 MB |
| 7. CNN Code Preparation (part 2).srt | 10.4 KB |
| 8. CNN Code Preparation (part 3).mp4 | 33.7 MB |
| 8. CNN Code Preparation (part 3).srt | 7.2 KB |
| 9. CNN for Fashion MNIST.mp4 | 74.5 MB |
| 9. CNN for Fashion MNIST.srt | 13.5 KB |
| 10. CNN for CIFAR-10.mp4 | 56.7 MB |
| 10. CNN for CIFAR-10.srt | 9.3 KB |
| 11. Data Augmentation.mp4 | 44.5 MB |
| 11. Data Augmentation.srt | 12.5 KB |
| 12. Batch Normalization.mp4 | 23.4 MB |
| 12. Batch Normalization.srt | 6.6 KB |
| 13. Improving CIFAR-10 Results.mp4 | 77.4 MB |
| 13. Improving CIFAR-10 Results.srt | 12.8 KB |
| 1. Sequence Data.mp4 | 114.3 MB |
| 1. Sequence Data.srt | 29.6 KB |
| 2. Forecasting.mp4 | 48.7 MB |
| 2. Forecasting.srt | 13.2 KB |
| 3. Autoregressive Linear Model for Time Series Prediction.mp4 | 81.2 MB |
| 3. Autoregressive Linear Model for Time Series Prediction.srt | 14.7 KB |
| 4. Proof that the Linear Model Works.mp4 | 17.9 MB |
| 4. Proof that the Linear Model Works.srt | 4.6 KB |
| 5. Recurrent Neural Networks.mp4 | 92.6 MB |
| 5. Recurrent Neural Networks.srt | 25.7 KB |
| 6. RNN Code Preparation.mp4 | 55.3 MB |
| 6. RNN Code Preparation.srt | 17.6 KB |
| 7. RNN for Time Series Prediction.mp4 | 71.9 MB |
| 7. RNN for Time Series Prediction.srt | 9.9 KB |
| 8. Paying Attention to Shapes.mp4 | 56.4 MB |
| 8. Paying Attention to Shapes.srt | 11.0 KB |
| 9. GRU and LSTM (pt 1).mp4 | 76.1 MB |
| 9. GRU and LSTM (pt 1).srt | 21.1 KB |
| 10. GRU and LSTM (pt 2).mp4 | 50.6 MB |
| 10. GRU and LSTM (pt 2).srt | 15.0 KB |
| 11. A More Challenging Sequence.mp4 | 86.7 MB |
| 11. A More Challenging Sequence.srt | 10.7 KB |
| 12. RNN for Image Classification (Theory).mp4 | 32.3 MB |
| 12. RNN for Image Classification (Theory).srt | 6.0 KB |
| 13. RNN for Image Classification (Code).mp4 | 20.5 MB |
| 13. RNN for Image Classification (Code).srt | 3.3 KB |
| 14. Stock Return Predictions using LSTMs (pt 1).mp4 | 77.8 MB |
| 14. Stock Return Predictions using LSTMs (pt 1).srt | 16.0 KB |
| 15. Stock Return Predictions using LSTMs (pt 2).mp4 | 43.2 MB |
| 15. Stock Return Predictions using LSTMs (pt 2).srt | 6.8 KB |
| 16. Stock Return Predictions using LSTMs (pt 3).mp4 | 71.1 MB |
| 16. Stock Return Predictions using LSTMs (pt 3).srt | 14.4 KB |
| 17. Other Ways to Forecast.mp4 | 28.3 MB |
| 17. Other Ways to Forecast.srt | 7.2 KB |
| 1. Embeddings.mp4 | 60.0 MB |
| 1. Embeddings.srt | 16.1 KB |
| 2. Neural Networks with Embeddings.mp4 | 15.6 MB |
| 2. Neural Networks with Embeddings.srt | 4.5 KB |
| 3. Text Preprocessing (pt 1).mp4 | 52.3 MB |
| 3. Text Preprocessing (pt 1).srt | 17.9 KB |
| 4. Text Preprocessing (pt 2).mp4 | 44.4 MB |
| 4. Text Preprocessing (pt 2).srt | 15.3 KB |
| 5. Text Preprocessing (pt 3).mp4 | 47.7 MB |
| 5. Text Preprocessing (pt 3).srt | 9.4 KB |
| 6. Text Classification with LSTMs.mp4 | 65.0 MB |
| 6. Text Classification with LSTMs.srt | 10.3 KB |
| 7. CNNs for Text.mp4 | 58.7 MB |
| 7. CNNs for Text.srt | 14.9 KB |
| 8. Text Classification with CNNs.mp4 | 39.3 MB |
| 8. Text Classification with CNNs.srt | 5.6 KB |
| 9. VIP Making Predictions with a Trained NLP Model.mp4 | 48.8 MB |
| 9. VIP Making Predictions with a Trained NLP Model.srt | 9.1 KB |
| 1. Recommender Systems with Deep Learning Theory.mp4 | 64.8 MB |
| 1. Recommender Systems with Deep Learning Theory.srt | 13.7 KB |
| 2. Recommender Systems with Deep Learning Code Preparation.mp4 | 40.1 MB |
| 2. Recommender Systems with Deep Learning Code Preparation.srt | 12.7 KB |
| 3. Recommender Systems with Deep Learning Code (pt 1).mp4 | 69.6 MB |
| 3. Recommender Systems with Deep Learning Code (pt 1).srt | 10.9 KB |
| 4. Recommender Systems with Deep Learning Code (pt 2).mp4 | 76.9 MB |
| 4. Recommender Systems with Deep Learning Code (pt 2).srt | 17.4 KB |
| 5. VIP Making Predictions with a Trained Recommender Model.mp4 | 32.7 MB |
| 5. VIP Making Predictions with a Trained Recommender Model.srt | 6.0 KB |
| 1. Transfer Learning Theory.mp4 | 58.2 MB |
| 1. Transfer Learning Theory.srt | 10.7 KB |
| 2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4 | 21.7 MB |
| 2. Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).srt | 5.2 KB |
| 3. Large Datasets.mp4 | 41.3 MB |
| 3. Large Datasets.srt | 9.1 KB |
| 4. 2 Approaches to Transfer Learning.mp4 | 21.8 MB |
| 4. 2 Approaches to Transfer Learning.srt | 6.0 KB |
| 5. Transfer Learning Code (pt 1).mp4 | 77.8 MB |
| 5. Transfer Learning Code (pt 1).srt | 11.6 KB |
| 6. Transfer Learning Code (pt 2).mp4 | 56.3 MB |
| 6. Transfer Learning Code (pt 2).srt | 8.8 KB |
| 1. GAN Theory.mp4 | 92.1 MB |
| 1. GAN Theory.srt | 21.1 KB |
| 2. GAN Code Preparation.mp4 | 28.1 MB |
| 2. GAN Code Preparation.srt | 8.5 KB |
| 3. GAN Code.mp4 | 61.4 MB |
| 3. GAN Code.srt | 10.7 KB |
| 1. Deep Reinforcement Learning Section Introduction.mp4 | 40.7 MB |
| 1. Deep Reinforcement Learning Section Introduction.srt | 8.6 KB |
| 2. Elements of a Reinforcement Learning Problem.mp4 | 104.9 MB |
| 2. Elements of a Reinforcement Learning Problem.srt | 26.2 KB |
| 3. States, Actions, Rewards, Policies.mp4 | 44.1 MB |
| 3. States, Actions, Rewards, Policies.srt | 11.3 KB |
| 4. Markov Decision Processes (MDPs).mp4 | 50.5 MB |
| 4. Markov Decision Processes (MDPs).srt | 12.7 KB |
| 5. The Return.mp4 | 23.4 MB |
| 5. The Return.srt | 6.3 KB |
| 6. Value Functions and the Bellman Equation.mp4 | 47.7 MB |
| 6. Value Functions and the Bellman Equation.srt | 12.5 KB |
| 7. What does it mean to “learn”.mp4 | 32.5 MB |
| 7. What does it mean to “learn”.srt | 8.9 KB |
| 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 | 42.6 MB |
| 8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt | 12.7 KB |
| 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 | 57.0 MB |
| 9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt | 14.9 KB |
| 10. Epsilon-Greedy.mp4 | 41.5 MB |
| 10. Epsilon-Greedy.srt | 7.4 KB |
| 11. Q-Learning.mp4 | 66.8 MB |
| 11. Q-Learning.srt | 17.9 KB |
| 12. Deep Q-Learning DQN (pt 1).mp4 | 60.2 MB |
| 12. Deep Q-Learning DQN (pt 1).srt | 16.4 KB |
| 13. Deep Q-Learning DQN (pt 2).mp4 | 52.2 MB |
| 13. Deep Q-Learning DQN (pt 2).srt | 13.2 KB |
| 14. How to Learn Reinforcement Learning.mp4 | 40.3 MB |
| 14. How to Learn Reinforcement Learning.srt | 7.6 KB |
| 1. Reinforcement Learning Stock Trader Introduction.mp4 | 28.8 MB |
| 1. Reinforcement Learning Stock Trader Introduction.srt | 6.8 KB |
| 2. Data and Environment.mp4 | 55.7 MB |
| 2. Data and Environment.srt | 15.7 KB |
| 3. Replay Buffer.mp4 | 25.0 MB |
| 3. Replay Buffer.srt | 6.9 KB |
| 4. Program Design and Layout.mp4 | 26.9 MB |
| 4. Program Design and Layout.srt | 8.6 KB |
| 5. Code pt 1.mp4 | 66.3 MB |
| 5. Code pt 1.srt | 12.1 KB |
| 6. Code pt 2.mp4 | 70.0 MB |
| 6. Code pt 2.srt | 11.8 KB |
| 7. Code pt 3.mp4 | 58.6 MB |
| 7. Code pt 3.srt | 8.4 KB |
| 8. Code pt 4.mp4 | 52.3 MB |
| 8. Code pt 4.srt | 8.2 KB |
| 9. Reinforcement Learning Stock Trader Discussion.mp4 | 17.2 MB |
| 9. Reinforcement Learning Stock Trader Discussion.srt | 4.4 KB |
| 1. Custom Loss and Estimating Prediction Uncertainty.mp4 | 43.6 MB |
| 1. Custom Loss and Estimating Prediction Uncertainty.srt | 12.8 KB |
| 2. Estimating Prediction Uncertainty Code.mp4 | 42.7 MB |
| 2. Estimating Prediction Uncertainty Code.srt | 8.8 KB |
| 1. Facial Recognition Section Introduction.mp4 | 24.3 MB |
| 1. Facial Recognition Section Introduction.srt | 4.6 KB |
| 2. Siamese Networks.mp4 | 50.5 MB |
| 2. Siamese Networks.srt | 12.8 KB |
| 3. Code Outline.mp4 | 23.9 MB |
| 3. Code Outline.srt | 5.8 KB |
| 4. Loading in the data.mp4 | 35.1 MB |
| 4. Loading in the data.srt | 6.9 KB |
| 5. Splitting the data into train and test.mp4 | 26.3 MB |
| 5. Splitting the data into train and test.srt | 5.1 KB |
| 6. Converting the data into pairs.mp4 | 30.4 MB |
| 6. Converting the data into pairs.srt | 5.8 KB |
| 7. Generating Generators.mp4 | 32.4 MB |
| 7. Generating Generators.srt | 5.7 KB |
| 8. Creating the model and loss.mp4 | 29.4 MB |
| 8. Creating the model and loss.srt | 5.4 KB |
| 9. Accuracy and imbalanced classes.mp4 | 51.1 MB |
| 9. Accuracy and imbalanced classes.srt | 9.5 KB |
| 10. Facial Recognition Section Summary.mp4 | 18.3 MB |
| 10. Facial Recognition Section Summary.srt | 4.4 KB |
| 1. Mean Squared Error.mp4 | 33.8 MB |
| 1. Mean Squared Error.srt | 11.2 KB |
| 2. Binary Cross Entropy.mp4 | 23.7 MB |
| 2. Binary Cross Entropy.srt | 7.3 KB |
| 3. Categorical Cross Entropy.mp4 | 31.7 MB |
| 3. Categorical Cross Entropy.srt | 9.6 KB |
| 1. Gradient Descent.mp4 | 34.9 MB |
| 1. Gradient Descent.srt | 9.8 KB |
| 2. Stochastic Gradient Descent.mp4 | 23.0 MB |
| 2. Stochastic Gradient Descent.srt | 5.4 KB |
| 3. Momentum.mp4 | 34.2 MB |
| 3. Momentum.srt | 7.8 KB |
| 4. Variable and Adaptive Learning Rates.mp4 | 34.9 MB |
| 4. Variable and Adaptive Learning Rates.srt | 15.2 KB |
| 5. Adam.mp4 | 38.9 MB |
| 5. Adam.srt | 13.5 KB |
| 1. Links To Colab Notebooks.html | 7.2 KB |
| 2. Links to VIP Notebooks.html | 256 bytes |
| 1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 150.7 MB |
| 1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt | 14.7 KB |
| READ_ME.txt | 404 bytes |
| 2. Windows-Focused Environment Setup 2018.srt | 20.0 KB |
| 3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 | 167.3 MB |
| 3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.srt | 32.0 KB |
| 1. What is the Appendix.mp4 | 16.4 MB |
| 1. What is the Appendix.srt | 3.7 KB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 105.7 MB |
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt | 31.6 KB |
| 3. How to Code Yourself (part 1).mp4 | 71.9 MB |
| 4. How to Code Yourself (part 2).mp4 | 49.2 MB |
| 4. How to Code Yourself (part 2).srt | 13.0 KB |
| 5. Proof that using Jupyter Notebook is the same as not using it.mp4 | 69.5 MB |
| 5. Proof that using Jupyter Notebook is the same as not using it.srt | 14.2 KB |
| 6. How to Succeed in this Course (Long Version).mp4 | 35.2 MB |
| 6. How to Succeed in this Course (Long Version).srt | 14.6 KB |
| 7. What order should I take your courses in (part 1).mp4 | 79.6 MB |
| 7. What order should I take your courses in (part 1).srt | 16.1 KB |
| 8. What order should I take your courses in (part 2).mp4 | 108.2 MB |
| 8. What order should I take your courses in (part 2).srt | 23.0 KB |
| 9. BONUS Where to get discount coupons and FREE deep learning material.mp4 | 37.8 MB |
| 9. BONUS Where to get discount coupons and FREE deep learning material.srt | 7.9 KB |
Name
DL
Uploader
Size
S/L
Added
-
15.9 GB
[83
/
15]
2023-07-01
| Uploaded by Prom3th3uS | Size 15.9 GB | Health [ 83 /15 ] | Added 2023-07-01 |
NOTE
SOURCE: PyTorch Deep Learning and Artificial Intelligence updated
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COVER
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